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Performance environnementale et mesure de la productivité

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  • Dubrocard, Anne
  • Prombo, Michel

Abstract

The study results presented here are derived from a process whose purpose was the initial deployment and use of the data envelopment analysis techniques and linear programming in R environment to verify the feasibility of transferring tools supporting analyzes conducted after the project Luxklems. The results and their theoretical subtended are presented in brief but show the possibilities and flexibility offered by the R environment to treat optimization problems. The focus is on the evolution of the Malmquist index when considering the undesirable outputs and also seeks to compare the results with and without consideration of environmental performance in in theoretical and empirical exercise covering 15 European countries and the United States. This approach uses for purposes of calculation, the strengths of the R language and some packages dealing with linear programming and directional distance functions. Thus, programs have been developed and adapted to extend the measurement of total factor productivity and its components - technical progress and technical efficiency – to take in account the environmental performance by minimizing infeasibility problems encountered in the usual approaches using Malmquist indices. Indeed, faced with the need to take into account the effects of production on the environment and more generally the urgency to find the path of sustainable development, many attempts have been made to reinforce measures productivity growth including the negative impact of pollution that the production of goods and services generates.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 41456.

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Date of creation: 20 Sep 2012
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Handle: RePEc:pra:mprapa:41456

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Related research

Keywords: Environmental performance; Data envelopment analysis (DEA); Undesirable output; Return to scale; Sequential Malmquist-Luenberger index; Malmquist-Luenberger index;

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  1. Luenberger, David G, 1996. "Welfare from a Benefit Viewpoint," Economic Theory, Springer, vol. 7(3), pages 445-62, April.
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  8. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
  9. Zofio, Jose L. & Prieto, Angel M., 2001. "Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries," Resource and Energy Economics, Elsevier, vol. 23(1), pages 63-83, January.
  10. Kumar, Surender, 2006. "Environmentally sensitive productivity growth: A global analysis using Malmquist-Luenberger index," Ecological Economics, Elsevier, vol. 56(2), pages 280-293, February.
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  12. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.
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